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marvin.fns.extract

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Constants

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DEFAULT_PROMPT

DEFAULT_PROMPT = "'\nYou are an expert entity extractor that always maintains as much semantic\nmeaning as possible. You use inference or deduction whenever necessary to\nsupply missing or omitted data. Examine the provided `data`, text, or\ninformation and generate a list of any entities or objects that match the\nrequested format.\n\n- When providing integers, do not write out any decimals at all\n- Use deduction where appropriate e.g. "3 dollars fifty cents" is a single\n    value [3.5] not two values [3, 50] unless the user specifically asks for\n    each part.'"

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PROMPT

PROMPT = DEFAULT_PROMPT

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T

T = TypeVar('T')

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Functions

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extract

def extract(data: Any, target: TargetType[T] | None = None, instructions: str | None = None, agent: Agent | None = None, thread: Thread | str | None = None, context: dict[str, Any] | None = None, handlers: list[Handler | AsyncHandler] | None = None, prompt: str | None = None) -> list[T]
Extracts entities of a specific type from the provided data. This function uses a language model to identify and extract entities of the specified type from the input data. The extracted entities are returned as a list. Args: data: The input data to extract entities from. Can be any type. target: The type of entities to extract. Defaults to str. instructions: Optional additional instructions to guide the extraction. Used to provide specific guidance about what to extract or how to process the data. Required when target is str. agent: Optional custom agent to use for extraction. If not provided, the default agent will be used. thread: Optional thread for maintaining conversation context. Can be either a Thread object or a string thread ID. context: Optional dictionary of additional context to include in the task. handlers: Optional list of handlers to use for the task. prompt: Optional prompt to use for the task. If not provided, the default prompt will be used. Returns: A list of extracted entities of type T. Raises: ValueError: If target is str and no instructions are provided.

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extract_async

def extract_async(data: Any, target: TargetType[T] | None = None, instructions: str | None = None, agent: Agent | None = None, thread: Thread | str | None = None, context: dict[str, Any] | None = None, handlers: list[Handler | AsyncHandler] | None = None, prompt: str | None = None) -> list[T]
Extracts entities of a specific type from the provided data. This function uses a language model to identify and extract entities of the specified type from the input data. The extracted entities are returned as a list. Args: data: The input data to extract entities from. Can be any type. target: The type of entities to extract. Defaults to str. instructions: Optional additional instructions to guide the extraction. Used to provide specific guidance about what to extract or how to process the data. Required when target is str. agent: Optional custom agent to use for extraction. If not provided, the default agent will be used. thread: Optional thread for maintaining conversation context. Can be either a Thread object or a string thread ID. context: Optional dictionary of additional context to include in the task. handlers: Optional list of handlers to use for the task. prompt: Optional prompt to use for the task. If not provided, the default prompt will be used. Returns: A list of extracted entities of type T. Raises: ValueError: If target is str and no instructions are provided.
Parent Module: fns